def _check_sdss_files(sdss, run, camcol, field, bandname, filetypes,
retrieve=True, tryopen=False):
from astrometry.sdss import band_index
bandnum = band_index(bandname)
for filetype in filetypes:
fn = sdss.getPath(filetype, run, camcol, field, bandname)
print('Looking for file', fn)
exists = os.path.exists(fn)
retrieveKwargs = {}
if exists and tryopen:
import pyfits
# This doesn't catch *all* types of errors you can imagine...
try:
T = pyfits.open(fn)
except:
print('Failed to open file', fn, 'as FITS file: maybe corrupt.')
exists = False
retrieveKwargs.update(skipExisting=False)
if (not exists) and retrieve:
print('Retrieving', fn)
res = sdss.retrieve(filetype, run, camcol, field, bandnum,
**retrieveKwargs)
if res is False:
raise RuntimeError('No such file on SDSS DAS: %s, ' % filetype +
'rcfb %i/%i/%i/%s' %
(run, camcol, field, bandname))
elif not exists:
raise os.OSError('no such file: "%s"' % fn)
def __init__(self, tsfield, bandname):
from astrometry.sdss import band_index
self.bandname = bandname
self.band = band_index(bandname)
#self.tsfield = tsfield
band = self.band
self.exptime = tsfield.exptime
self.aa = tsfield.aa[band]
self.kk = tsfield.kk[band]
self.airmass = tsfield.airmass[band]
super(SdssMagsPhotoCal, self).__init__()
def __init__(self, tsfield, bandname):
from astrometry.sdss import band_index
self.bandname = bandname
self.band = band_index(bandname)
#self.tsfield = tsfield
band = self.band
self.exptime = tsfield.exptime
self.aa = tsfield.aa[band]
self.kk = tsfield.kk[band]
self.airmass = tsfield.airmass[band]
super(SdssMagsPhotoCal,self).__init__()
def sdss_coadd(targetwcs, bands):
from astrometry.sdss import DR9, band_index
from astrometry.sdss import AsTransWrapper
#sdss = DR9(basedir=photoobjdir)
#sdss.useLocalTree()
sdss = DR9(basedir='tmp')
sdss.saveUnzippedFiles('tmp')
#wfn = sdss.filenames.get('window_flist', None)
wfn = os.path.join(os.environ.get('PHOTO_RESOLVE', ''),
'window_flist.fits')
from astrometry.sdss.fields import radec_to_sdss_rcf
ra, dec = targetwcs.radec_center()
rad = targetwcs.radius()
rad = rad + np.hypot(10., 14.) / 2. / 60.
print('Searching for run,camcol,fields with radius', rad, 'deg')
RCF = radec_to_sdss_rcf(ra, dec, radius=rad * 60., tablefn=wfn)
print('Found %i fields possibly in range' % len(RCF))
H, W = targetwcs.shape
sdsscoimgs = [np.zeros((H, W), np.float32) for band in bands]
sdsscons = [np.zeros((H, W), np.float32) for band in bands]
for run, camcol, field, r, d in RCF:
for iband, band in enumerate(bands):
bandnum = band_index(band)
sdss.retrieve('frame', run, camcol, field, band)
frame = sdss.readFrame(run, camcol, field, bandnum)
print('Got frame', frame)
h, w = frame.getImageShape()
simg = frame.getImage()
wcs = AsTransWrapper(frame.astrans, w, h, 0.5, 0.5)
try:
Yo, Xo, Yi, Xi, nil = resample_with_wcs(targetwcs, wcs)
except OverlapError:
continue
sdsscoimgs[iband][Yo, Xo] += simg[Yi, Xi]
sdsscons[iband][Yo, Xo] += 1
for co, n in zip(sdsscoimgs, sdsscons):
co /= np.maximum(1e-6, n)
return sdsscoimgs, sdsscons
def sdss_coadd(targetwcs, bands):
from astrometry.sdss import DR9, band_index
from astrometry.sdss import AsTransWrapper
#sdss = DR9(basedir=photoobjdir)
#sdss.useLocalTree()
sdss = DR9(basedir='tmp')
sdss.saveUnzippedFiles('tmp')
#wfn = sdss.filenames.get('window_flist', None)
wfn = os.path.join(os.environ.get('PHOTO_RESOLVE',''), 'window_flist.fits')
from astrometry.sdss.fields import radec_to_sdss_rcf
ra,dec = targetwcs.radec_center()
rad = targetwcs.radius()
rad = rad + np.hypot(10.,14.)/2./60.
print 'Searching for run,camcol,fields with radius', rad, 'deg'
RCF = radec_to_sdss_rcf(ra, dec, radius=rad*60., tablefn=wfn)
print 'Found %i fields possibly in range' % len(RCF)
H,W = targetwcs.shape
sdsscoimgs = [np.zeros((H,W),np.float32) for band in bands]
sdsscons = [np.zeros((H,W),np.float32) for band in bands]
for run,camcol,field,r,d in RCF:
for iband,band in enumerate(bands):
bandnum = band_index(band)
sdss.retrieve('frame', run, camcol, field, band)
frame = sdss.readFrame(run, camcol, field, bandnum)
print 'Got frame', frame
h,w = frame.getImageShape()
simg = frame.getImage()
wcs = AsTransWrapper(frame.astrans, w, h, 0.5, 0.5)
try:
Yo,Xo,Yi,Xi,nil = resample_with_wcs(targetwcs, wcs, [], 3)
except OverlapError:
continue
sdsscoimgs[iband][Yo,Xo] += simg[Yi,Xi]
sdsscons [iband][Yo,Xo] += 1
for co,n in zip(sdsscoimgs, sdsscons):
co /= np.maximum(1e-6, n)
return sdsscoimgs, sdsscons
def _check_sdss_files(sdss,
run,
camcol,
field,
bandname,
filetypes,
retrieve=True,
tryopen=False):
from astrometry.sdss import band_index
bandnum = band_index(bandname)
for filetype in filetypes:
fn = sdss.getPath(filetype, run, camcol, field, bandname)
print('Looking for file', fn)
exists = os.path.exists(fn)
retrieveKwargs = {}
if exists and tryopen:
# This doesn't catch *all* types of errors you can imagine...
cmd = 'fitsverify -q %s' % fn
try:
print('Running:', cmd)
rtn = os.system(cmd)
print('rtn:', rtn)
if rtn != 0:
exists = False
except:
print('Failed to fitsverify', fn, ': maybe corrupt.')
exists = False
if not exists:
retrieveKwargs.update(skipExisting=False)
if (not exists) and retrieve:
print('Retrieving', fn)
res = sdss.retrieve(filetype, run, camcol, field, bandnum,
**retrieveKwargs)
if res is False:
raise RuntimeError('No such file on SDSS DAS: %s, ' %
filetype + 'rcfb %i/%i/%i/%s' %
(run, camcol, field, bandname))
elif not exists:
raise OSError('no such file: "%s", or failed to verify' % fn)
def _check_sdss_files(sdss,
run,
camcol,
field,
bandname,
filetypes,
retrieve=True,
tryopen=False):
from astrometry.sdss import band_index
bandnum = band_index(bandname)
for filetype in filetypes:
fn = sdss.getPath(filetype, run, camcol, field, bandname)
print('Looking for file', fn)
exists = os.path.exists(fn)
retrieveKwargs = {}
if exists and tryopen:
import pyfits
# This doesn't catch *all* types of errors you can imagine...
try:
T = pyfits.open(fn)
except:
print('Failed to open file', fn,
'as FITS file: maybe corrupt.')
exists = False
retrieveKwargs.update(skipExisting=False)
if (not exists) and retrieve:
print('Retrieving', fn)
res = sdss.retrieve(filetype, run, camcol, field, bandnum,
**retrieveKwargs)
if res is False:
raise RuntimeError('No such file on SDSS DAS: %s, ' %
filetype + 'rcfb %i/%i/%i/%s' %
(run, camcol, field, bandname))
elif not exists:
raise os.OSError('no such file: "%s"' % fn)
def get_tractor_image_dr7(run, camcol, field, bandname,
sdssobj=None, release='DR7',
retrieve=True, curl=False,
psf='kl-gm', useMags=False,
roi=None,
roiradecsize=None,
roiradecbox=None,
nanomaggies=False,
savepsfimg=None, zrange=[-3, 10]):
'''
Creates a tractor.Image given an SDSS field identifier.
If not None, roi = (x0, x1, y0, y1) defines a region-of-interest
in the image, in zero-indexed pixel coordinates. x1,y1 are
NON-inclusive; roi=(0,100,0,100) will yield a 100 x 100 image.
psf can be:
"dg" for double-Gaussian
"kl-gm" for SDSS KL-decomposition approximated as a Gaussian mixture
"roiradecsize" = (ra, dec, half-size in pixels) indicates that you
want to grab a ROI around the given RA,Dec.
Returns:
(tractor.Image, dict)
dict contains useful details like:
'sky'
'skysig'
'''
from astrometry.sdss import DR7, band_index
if sdssobj is None:
# Ugly
if release != 'DR7':
raise RuntimeError('We only support DR7 currently')
sdss = DR7(curl=curl)
else:
sdss = sdssobj
valid_psf = ['dg', 'kl-gm']
if psf not in valid_psf:
raise RuntimeError('PSF must be in ' + str(valid_psf))
# FIXME
rerun = 0
bandnum = band_index(bandname)
_check_sdss_files(sdss, run, camcol, field, bandname,
['fpC', 'tsField', 'psField', 'fpM'],
retrieve=retrieve)
fpC = sdss.readFpC(run, camcol, field, bandname)
hdr = fpC.getHeader()
fpC = fpC.getImage()
fpC = fpC.astype(np.float32) - sdss.softbias
image = fpC
(H, W) = image.shape
info = dict()
tai = hdr.get('TAI')
stripe = hdr.get('STRIPE')
strip = hdr.get('STRIP')
obj = hdr.get('OBJECT')
info.update(tai=tai, stripe=stripe, strip=strip, object=obj, hdr=hdr)
tsf = sdss.readTsField(run, camcol, field, rerun)
astrans = tsf.getAsTrans(bandnum)
wcs = SdssWcs(astrans)
#print('Created SDSS Wcs:', wcs)
X = interpret_roi(wcs, (H, W), roi=roi, roiradecsize=roiradecsize,
roiradecbox=roiradecbox)
if X is None:
return None, None
roi, hasroi = X
info.update(roi=roi)
x0, x1, y0, y1 = roi
# Mysterious half-pixel shift. asTrans pixel coordinates?
wcs.setX0Y0(x0 + 0.5, y0 + 0.5)
if nanomaggies:
zp = tsf.get_zeropoint(bandnum)
photocal = LinearPhotoCal(NanoMaggies.zeropointToScale(zp),
band=bandname)
elif useMags:
photocal = SdssMagsPhotoCal(tsf, bandname)
else:
photocal = SdssFluxPhotoCal()
psfield = sdss.readPsField(run, camcol, field)
sky = psfield.getSky(bandnum)
skysig = sqrt(sky)
skyobj = ConstantSky(sky)
zr = sky + np.array(zrange) * skysig
info.update(sky=sky, skysig=skysig, zr=zr)
fpM = sdss.readFpM(run, camcol, field, bandname)
gain = psfield.getGain(bandnum)
darkvar = psfield.getDarkVariance(bandnum)
skyerr = psfield.getSkyErr(bandnum)
invvar = sdss.getInvvar(fpC, fpM, gain, darkvar, sky, skyerr)
dgpsf = psfield.getDoubleGaussian(bandnum, normalize=True)
info.update(dgpsf=dgpsf)
if roi is not None:
roislice = (slice(y0, y1), slice(x0, x1))
image = image[roislice].copy()
invvar = invvar[roislice].copy()
if psf == 'kl-gm':
from emfit import em_fit_2d
from fitpsf import em_init_params
# Create Gaussian mixture model PSF approximation.
H, W = image.shape
klpsf = psfield.getPsfAtPoints(bandnum, x0 + W / 2, y0 + H / 2)
S = klpsf.shape[0]
# number of Gaussian components
K = 3
w, mu, sig = em_init_params(K, None, None, None)
II = klpsf.copy()
II /= II.sum()
# HIDEOUS HACK
II = np.maximum(II, 0)
#print('Multi-Gaussian PSF fit...')
xm, ym = -(S / 2), -(S / 2)
if savepsfimg is not None:
plt.clf()
plt.imshow(II, interpolation='nearest', origin='lower')
plt.title('PSF image to fit with EM')
plt.savefig(savepsfimg)
res = em_fit_2d(II, xm, ym, w, mu, sig)
print('em_fit_2d result:', res)
if res == 0:
# print('w,mu,sig', w,mu,sig)
mypsf = GaussianMixturePSF(w, mu, sig)
mypsf.computeRadius()
else:
# Failed! Return 'dg' model instead?
print('PSF model fit', psf, 'failed! Returning DG model instead')
psf = 'dg'
if psf == 'dg':
print('Creating double-Gaussian PSF approximation')
(a, s1, b, s2) = dgpsf
mypsf = NCircularGaussianPSF([s1, s2], [a, b])
timg = Image(data=image, invvar=invvar, psf=mypsf, wcs=wcs,
sky=skyobj, photocal=photocal,
name=('SDSS (r/c/f/b=%i/%i/%i/%s)' %
(run, camcol, field, bandname)))
timg.zr = zr
return timg, info
def _get_tractor_image_dr8(run,
camcol,
field,
bandname,
sdss=None,
roi=None,
psf='kl-gm',
roiradecsize=None,
roiradecbox=None,
savepsfimg=None,
curl=False,
nanomaggies=False,
zrange=[-3, 10],
invvarIgnoresSourceFlux=False,
invvarAtCenter=False,
invvarAtCenterImage=False,
retrieve=True,
imargs={}):
from astrometry.sdss import band_index
origpsf = psf
if psf.startswith('bright-'):
psf = psf[7:]
brightpsf = True
print('Setting bright PSF handling')
else:
brightpsf = False
valid_psf = ['dg', 'kl-gm', 'kl-pix']
if psf not in valid_psf:
raise RuntimeError('PSF must be in ' + str(valid_psf))
if sdss is None:
from astrometry.sdss import DR8
sdss = DR8(curl=curl)
bandnum = band_index(bandname)
if retrieve:
for ft in ['psField', 'fpM']:
fn = sdss.retrieve(ft, run, camcol, field, bandname)
fn = sdss.retrieve('frame', run, camcol, field, bandname)
else:
fn = sdss.getPath('frame', run, camcol, field, bandname)
# http://data.sdss3.org/datamodel/files/BOSS_PHOTOOBJ/frames/RERUN/RUN/CAMCOL/frame.html
frame = sdss.readFrame(run, camcol, field, bandname, filename=fn)
H, W = frame.getImageShape()
info = dict()
hdr = frame.getHeader()
tai = hdr.get('TAI')
stripe = hdr.get('STRIPE')
strip = hdr.get('STRIP')
obj = hdr.get('OBJECT')
info.update(tai=tai, stripe=stripe, strip=strip, object=obj, hdr=hdr)
astrans = frame.getAsTrans()
wcs = SdssWcs(astrans)
#print('Created SDSS Wcs:', wcs)
#print('(x,y) = 1,1 -> RA,Dec', wcs.pixelToPosition(1,1))
X = interpret_roi(wcs, (H, W),
roi=roi,
roiradecsize=roiradecsize,
roiradecbox=roiradecbox)
if X is None:
return None, None
roi, hasroi = X
info.update(roi=roi)
x0, x1, y0, y1 = roi
# Half-pixel shift for asTrans pixel coordinates.
wcs.setX0Y0(x0 + 0.5, y0 + 0.5)
if nanomaggies:
photocal = LinearPhotoCal(1., band=bandname)
else:
photocal = MagsPhotoCal(bandname, 22.5)
sky = 0.
skyobj = ConstantSky(sky)
calibvec = frame.getCalibVec()
invvarAtCenter = invvarAtCenter or invvarAtCenterImage
psfield = sdss.readPsField(run, camcol, field)
iva = dict(ignoreSourceFlux=invvarIgnoresSourceFlux)
if invvarAtCenter:
if hasroi:
iva.update(constantSkyAt=(int((x0 + x1) / 2.),
int((y0 + y1) / 2.)))
else:
iva.update(constantSkyAt=(int(W / 2.), int(H / 2.)))
invvar = frame.getInvvar(psfield, bandnum, **iva)
invvar = invvar.astype(np.float32)
if not invvarAtCenter:
assert (invvar.shape == (H, W))
# Could get this from photoField instead
# http://data.sdss3.org/datamodel/files/BOSS_PHOTOOBJ/RERUN/RUN/photoField.html
gain = psfield.getGain(bandnum)
darkvar = psfield.getDarkVariance(bandnum)
meansky = np.mean(frame.sky)
meancalib = np.mean(calibvec)
skysig = sqrt((meansky / gain) + darkvar) * meancalib
info.update(sky=sky, skysig=skysig)
zr = np.array(zrange) * skysig + sky
info.update(zr=zr)
# http://data.sdss3.org/datamodel/files/PHOTO_REDUX/RERUN/RUN/objcs/CAMCOL/fpM.html
fpM = sdss.readFpM(run, camcol, field, bandname)
if not hasroi:
image = frame.getImage()
else:
roislice = (slice(y0, y1), slice(x0, x1))
image = frame.getImageSlice(roislice).astype(np.float32)
if invvarAtCenterImage:
invvar = invvar + np.zeros(image.shape, np.float32)
elif invvarAtCenter:
pass
else:
invvar = invvar[roislice].copy()
H, W = image.shape
if (not invvarAtCenter) or invvarAtCenterImage:
for plane in ['INTERP', 'SATUR', 'CR', 'GHOST']:
fpM.setMaskedPixels(plane, invvar, 0, roi=roi)
dgpsf = psfield.getDoubleGaussian(bandnum, normalize=True)
info.update(dgpsf=dgpsf)
if psf == 'kl-pix':
# Pixelized KL-PSF
klpsf = psfield.getPsfAtPoints(bandnum, x0 + W / 2, y0 + H / 2)
# Trim symmetric zeros
sh, sw = klpsf.shape
while True:
if (np.all(klpsf[0, :] == 0.) and np.all(klpsf[:, 0] == 0.)
and np.all(klpsf[-1, :] == 0.)
and np.all(klpsf[:, -1] == 0.)):
klpsf = klpsf[1:-1, 1:-1]
else:
break
mypsf = PixelizedPSF(klpsf)
elif psf == 'kl-gm':
from tractor.emfit import em_fit_2d
from tractor.fitpsf import em_init_params
# Create Gaussian mixture model PSF approximation.
klpsf = psfield.getPsfAtPoints(bandnum, x0 + W / 2, y0 + H / 2)
S = klpsf.shape[0]
# number of Gaussian components
K = 3
w, mu, sig = em_init_params(K, None, None, None)
II = klpsf.copy()
II /= II.sum()
# HIDEOUS HACK
II = np.maximum(II, 0)
#print('Multi-Gaussian PSF fit...')
xm, ym = -(S // 2), -(S // 2)
if savepsfimg is not None:
plt.clf()
plt.imshow(II, interpolation='nearest', origin='lower')
plt.title('PSF image to fit with EM')
plt.savefig(savepsfimg)
res = em_fit_2d(II, xm, ym, w, mu, sig)
#print('em_fit_2d result:', res)
if res == 0:
# print('w,mu,sig', w,mu,sig)
mypsf = GaussianMixturePSF(w, mu, sig)
mypsf.computeRadius()
else:
# Failed! Return 'dg' model instead?
print('PSF model fit', psf, 'failed! Returning DG model instead')
psf = 'dg'
if psf == 'dg':
print('Creating double-Gaussian PSF approximation')
(a, s1, b, s2) = dgpsf
mypsf = NCircularGaussianPSF([s1, s2], [a, b])
if brightpsf:
print('Wrapping PSF in SdssBrightPSF')
(a1, s1, a2, s2, a3, sigmap, beta) = psfield.getPowerLaw(bandnum)
mypsf = SdssBrightPSF(mypsf, a1, s1, a2, s2, a3, sigmap, beta)
print('PSF:', mypsf)
timg = Image(data=image,
invvar=invvar,
psf=mypsf,
wcs=wcs,
sky=skyobj,
photocal=photocal,
name=('SDSS (r/c/f/b=%i/%i/%i/%s)' %
(run, camcol, field, bandname)),
time=TAITime(tai),
**imargs)
timg.zr = zr
return timg, info
def _get_sources(run,
camcol,
field,
bandname='r',
sdss=None,
release='DR7',
objs=None,
retrieve=True,
checkFiles=True,
curl=False,
roi=None,
radecroi=None,
radecrad=None,
bands=None,
badmag=25,
nanomaggies=False,
getobjs=False,
getsourceobjs=False,
getobjinds=False,
extrabands=None,
fixedComposites=False,
forcePointSources=False,
useObjcType=False,
objCuts=True,
classmap={},
ellipse=GalaxyShape,
cutToPrimary=False):
'''
If set,
radecrad = (ra,dec,rad)
returns sources within "rad" degrees of the given RA,Dec (in degrees)
center.
WARNING, this method alters the "objs" argument, if given.
Consider calling objs.copy() before calling.
-"bandname" is the SDSS band used to cut on position, select
star/gal/exp/dev, and set galaxy shapes.
-"bands" are the bands to include in the returned Source objects;
they will be initialized from the SDSS bands.
-"extrabands" are also included in the returned Source objects;
they will be initialized to the SDSS flux for either the first of
"bands", if given, or "bandname".
'''
from astrometry.sdss import (DR7, DR8, DR9, band_names, band_index,
photo_flags1_map)
# brightPointSourceThreshold=0.):
if sdss is None:
dr = dict(DR7=DR7, DR8=DR8, DR9=DR9)[release]
sdss = dr(curl=curl)
drnum = sdss.getDRNumber()
isdr7 = (drnum == 7)
if bands is None:
bands = band_names()
bandnum = band_index(bandname)
bandnums = np.array([band_index(b) for b in bands])
bandnames = bands
if extrabands is None:
extrabands = []
if objs is None:
from astrometry.util.fits import fits_table
if isdr7:
# FIXME
rerun = 0
if checkFiles:
_check_sdss_files(sdss,
run,
camcol,
field,
bandnum, ['tsObj', 'tsField'],
retrieve=retrieve,
tryopen=True)
tsf = sdss.readTsField(run, camcol, field, rerun)
objfn = sdss.getPath('tsObj',
run,
camcol,
field,
bandname,
rerun=rerun)
else:
if checkFiles:
_check_sdss_files(sdss,
run,
camcol,
field,
bandnum, ['photoObj'],
retrieve=retrieve,
tryopen=True)
objfn = sdss.getPath('photoObj', run, camcol, field)
objs = fits_table(objfn)
if objs is None:
print('No sources in SDSS file', objfn)
return []
objs.index = np.arange(len(objs))
if getobjs:
allobjs = objs.copy()
if roi is not None:
x0, x1, y0, y1 = roi
# FIXME -- we keep only the sources whose centers are within
# the ROI box. Should instead do some ellipse-overlaps
# geometry.
x = objs.colc[:, bandnum]
y = objs.rowc[:, bandnum]
objs.cut((x >= x0) * (x < x1) * (y >= y0) * (y < y1))
if radecroi is not None:
r0, r1, d0, d1 = radecroi
objs.cut((objs.ra >= r0) * (objs.ra <= r1) * (objs.dec >= d0) *
(objs.dec <= d1))
if radecrad is not None:
from astrometry.libkd.spherematch import match_radec
(ra, dec, rad) = radecrad
I, J, d = match_radec(ra, dec, objs.ra, objs.dec, rad)
objs.cut(J)
del I
del d
if objCuts:
# Only deblended children;
# No BRIGHT sources
bright = photo_flags1_map.get('BRIGHT')
objs.cut((objs.nchild == 0) * ((objs.objc_flags & bright) == 0))
if cutToPrimary:
objs.cut((objs.resolve_status & 256) > 0)
if len(objs) == 0:
sources = []
if not (getobjs or getobjinds or getsourceobjs):
return sources
rtn = [sources]
if getobjs:
rtn.append(None)
if getobjinds:
rtn.append(None)
if getsourceobjs:
rtn.append(None)
return rtn
if isdr7:
objs.rename('phi_dev', 'phi_dev_deg')
objs.rename('phi_exp', 'phi_exp_deg')
objs.rename('r_dev', 'theta_dev')
objs.rename('r_exp', 'theta_exp')
# SDSS and Tractor have different opinions on which way this rotation goes
objs.phi_dev_deg *= -1.
objs.phi_exp_deg *= -1.
# MAGIC -- minimum size of galaxy.
objs.theta_dev = np.maximum(objs.theta_dev, 1. / 30.)
objs.theta_exp = np.maximum(objs.theta_exp, 1. / 30.)
if forcePointSources:
Lstar = np.ones(len(objs), float)
Lgal = np.zeros(len(objs), float)
Ldev = Lexp = Lgal
else:
if useObjcType:
objs.cut(np.logical_or(objs.objc_type == 6, objs.objc_type == 3))
Lstar = (objs.objc_type == 6)
Lgal = (objs.objc_type == 3)
else:
Lstar = (objs.prob_psf[:, bandnum] == 1) * 1.0
Lgal = (objs.prob_psf[:, bandnum] == 0) * 1.0
if isdr7:
fracdev = objs.fracpsf[:, bandnum]
else:
fracdev = objs.fracdev[:, bandnum]
Ldev = Lgal * fracdev
Lexp = Lgal * (1. - fracdev)
if isdr7:
from .sdss_dr7 import _dr7_getBrightness
if nanomaggies:
raise RuntimeError('Nanomaggies not supported for DR7 (yet)')
def lup2bright(lups):
counts = [
tsf.luptitude_to_counts(lup, j) for j, lup in enumerate(lups)
]
counts = np.array(counts)
bright = _dr7_getBrightness(counts, tsf, bandnames, extrabands)
return bright
flux2bright = lup2bright
starflux = objs.psfcounts
compflux = objs.counts_model
devflux = objs.counts_dev
expflux = objs.counts_exp
def comp2bright(lups, Ldev, Lexp):
counts = [
tsf.luptitude_to_counts(lup, j) for j, lup in enumerate(lups)
]
counts = np.array(counts)
dcounts = counts * Ldev
ecounts = counts * Lexp
dbright = _dr7_getBrightness(dcounts, tsf, bands, extrabands)
ebright = _dr7_getBrightness(ecounts, tsf, bands, extrabands)
return dbright, ebright
else:
def nmgy2bright(flux):
if len(bandnums):
flux = flux[bandnums]
else:
flux = flux[np.array([bandnum])]
bb = bandnames + extrabands
if nanomaggies:
if len(extrabands):
if len(bandnums) == 0:
# Only "extrabands", no SDSS bands.
flux = np.zeros(len(extrabands)) + flux[0]
else:
flux = np.append(flux, np.zeros(len(extrabands)))
bright = NanoMaggies(order=bb, **dict(zip(bb, flux)))
else:
I = (flux > 0)
mag = np.zeros_like(flux) + badmag
mag[I] = sdss.nmgy_to_mag(flux[I])
if len(extrabands):
mag = np.append(mag, np.zeros(len(extrabands)) + badmag)
bright = Mags(order=bb, **dict(zip(bb, mag)))
return bright
def comp2bright(flux, Ldev, Lexp):
dflux = flux * Ldev
eflux = flux * Lexp
dbright = nmgy2bright(dflux)
ebright = nmgy2bright(eflux)
return dbright, ebright
flux2bright = nmgy2bright
starflux = objs.psfflux
compflux = objs.cmodelflux
devflux = objs.devflux
expflux = objs.expflux
sources = []
nstars, ndev, nexp, ncomp = 0, 0, 0, 0
isources = []
ptsrcclass = classmap.get(PointSource, PointSource)
for i in range(len(objs)):
if Lstar[i]:
pos = RaDecPos(objs.ra[i], objs.dec[i])
flux = starflux[i, :]
bright = flux2bright(flux)
# This should work, I just don't feel like testing it now...
# if brightPointSourceThreshold:
# ps = SdssPointSource(pos, bright, thresh=brightPointSourceThreshold)
# else:
# ps = PointSource(pos, bright)
sources.append(ptsrcclass(pos, bright))
nstars += 1
isources.append(i)
continue
hasdev = (Ldev[i] > 0)
hasexp = (Lexp[i] > 0)
iscomp = (hasdev and hasexp)
pos = RaDecPos(objs.ra[i], objs.dec[i])
if iscomp:
flux = compflux[i, :]
elif hasdev:
flux = devflux[i, :]
elif hasexp:
flux = expflux[i, :]
else:
print(
'Skipping object with Lstar = %g, Ldev = %g, Lexp = %g (fracdev=%g)'
% (Lstar[i], Ldev[i], Lexp[i], fracdev[i]))
continue
isources.append(i)
if iscomp:
if fixedComposites:
bright = flux2bright(flux)
fdev = (Ldev[i] / (Ldev[i] + Lexp[i]))
else:
dbright, ebright = comp2bright(flux, Ldev[i], Lexp[i])
else:
bright = flux2bright(flux)
if hasdev:
re = objs.theta_dev[i, bandnum]
ab = objs.ab_dev[i, bandnum]
phi = objs.phi_dev_deg[i, bandnum]
dshape = ellipse(re, ab, phi)
if hasexp:
re = objs.theta_exp[i, bandnum]
ab = objs.ab_exp[i, bandnum]
phi = objs.phi_exp_deg[i, bandnum]
eshape = ellipse(re, ab, phi)
if iscomp:
if fixedComposites:
gal = FixedCompositeGalaxy(pos, bright, fdev, eshape, dshape)
else:
gal = CompositeGalaxy(pos, ebright, eshape, dbright, dshape)
ncomp += 1
elif hasdev:
gal = DevGalaxy(pos, bright, dshape)
ndev += 1
elif hasexp:
gal = ExpGalaxy(pos, bright, eshape)
nexp += 1
sources.append(gal)
print(
'Created',
ndev,
'deV,',
nexp,
'exp,',
ncomp,
'composite',
)
print('(total %i) galaxies and %i stars' % (ndev + nexp + ncomp, nstars))
if not (getobjs or getobjinds or getsourceobjs):
return sources
if nstars + ndev + nexp + ncomp < len(objs):
objs = objs[np.array(isources)]
rtn = [sources]
if getobjs:
rtn.append(allobjs)
if getobjinds:
rtn.append(objs.index if len(objs) else np.array([]))
if getsourceobjs:
rtn.append(objs)
return rtn
def _get_tractor_image_dr8(run, camcol, field, bandname, sdss=None,
roi=None, psf='kl-gm', roiradecsize=None,
roiradecbox=None,
savepsfimg=None, curl=False,
nanomaggies=False,
zrange=[-3,10],
invvarIgnoresSourceFlux=False,
invvarAtCenter=False,
invvarAtCenterImage=False,
imargs={}):
# retry_retrieve=True,
'''
Creates a tractor.Image given an SDSS field identifier.
If not None, roi = (x0, x1, y0, y1) defines a region-of-interest
in the image, in zero-indexed pixel coordinates. x1,y1 are
NON-inclusive; roi=(0,100,0,100) will yield a 100 x 100 image.
psf can be:
"dg" for double-Gaussian
"kl-gm" for SDSS KL-decomposition approximated as a Gaussian mixture
"bright-*", "*" one of the above PSFs, with special handling at
the bright end.
"roiradecsize" = (ra, dec, half-size in pixels) indicates that you
want to grab a ROI around the given RA,Dec.
"roiradecbox" = (ra0, ra1, dec0, dec1) indicates that you
want to grab a ROI containing the given RA,Dec ranges.
"invvarAtCentr" -- get a scalar constant inverse-variance
"invvarAtCenterImage" -- get a scalar constant inverse-variance
but still make an image out of it.
Returns: (tractor.Image, dict)
dict contains useful details like:
'sky'
'skysig'
'''
from astrometry.sdss import band_index
origpsf = psf
if psf.startswith('bright-'):
psf = psf[7:]
brightpsf = True
print('Setting bright PSF handling')
else:
brightpsf = False
valid_psf = ['dg', 'kl-gm', 'kl-pix']
if psf not in valid_psf:
raise RuntimeError('PSF must be in ' + str(valid_psf))
if sdss is None:
from astrometry.sdss import DR8
sdss = DR8(curl=curl)
bandnum = band_index(bandname)
for ft in ['psField', 'fpM']:
fn = sdss.retrieve(ft, run, camcol, field, bandname)
fn = sdss.retrieve('frame', run, camcol, field, bandname)
# http://data.sdss3.org/datamodel/files/BOSS_PHOTOOBJ/frames/RERUN/RUN/CAMCOL/frame.html
frame = sdss.readFrame(run, camcol, field, bandname, filename=fn)
#image = frame.getImage().astype(np.float32)
#(H,W) = image.shape
H,W = frame.getImageShape()
info = dict()
hdr = frame.getHeader()
tai = hdr.get('TAI')
stripe = hdr.get('STRIPE')
strip = hdr.get('STRIP')
obj = hdr.get('OBJECT')
info.update(tai=tai, stripe=stripe, strip=strip, object=obj, hdr=hdr)
astrans = frame.getAsTrans()
wcs = SdssWcs(astrans)
#print('Created SDSS Wcs:', wcs)
#print('(x,y) = 1,1 -> RA,Dec', wcs.pixelToPosition(1,1))
X = interpret_roi(wcs, (H,W), roi=roi, roiradecsize=roiradecsize,
roiradecbox=roiradecbox)
if X is None:
return None,None
roi,hasroi = X
info.update(roi=roi)
x0,x1,y0,y1 = roi
# Mysterious half-pixel shift. asTrans pixel coordinates?
wcs.setX0Y0(x0 + 0.5, y0 + 0.5)
if nanomaggies:
photocal = LinearPhotoCal(1., band=bandname)
else:
photocal = SdssNanomaggiesPhotoCal(bandname)
sky = 0.
skyobj = ConstantSky(sky)
calibvec = frame.getCalibVec()
invvarAtCenter = invvarAtCenter or invvarAtCenterImage
psfield = sdss.readPsField(run, camcol, field)
iva = dict(ignoreSourceFlux=invvarIgnoresSourceFlux)
if invvarAtCenter:
if hasroi:
iva.update(constantSkyAt=((x0+x1)/2., (y0+y1)/2.))
else:
iva.update(constantSkyAt=(W/2., H/2.))
invvar = frame.getInvvar(psfield, bandnum, **iva)
invvar = invvar.astype(np.float32)
if not invvarAtCenter:
assert(invvar.shape == (H,W))
# Could get this from photoField instead
# http://data.sdss3.org/datamodel/files/BOSS_PHOTOOBJ/RERUN/RUN/photoField.html
gain = psfield.getGain(bandnum)
darkvar = psfield.getDarkVariance(bandnum)
meansky = np.mean(frame.sky)
meancalib = np.mean(calibvec)
skysig = sqrt((meansky / gain) + darkvar) * meancalib
info.update(sky=sky, skysig=skysig)
zr = np.array(zrange)*skysig + sky
info.update(zr=zr)
# http://data.sdss3.org/datamodel/files/PHOTO_REDUX/RERUN/RUN/objcs/CAMCOL/fpM.html
fpM = sdss.readFpM(run, camcol, field, bandname)
if not hasroi:
image = frame.getImage()
else:
roislice = (slice(y0,y1), slice(x0,x1))
image = frame.getImageSlice(roislice).astype(np.float32)
if invvarAtCenterImage:
invvar = invvar + np.zeros(image.shape, np.float32)
elif invvarAtCenter:
pass
else:
invvar = invvar[roislice].copy()
H,W = image.shape
if (not invvarAtCenter) or invvarAtCenterImage:
for plane in [ 'INTERP', 'SATUR', 'CR', 'GHOST' ]:
fpM.setMaskedPixels(plane, invvar, 0, roi=roi)
dgpsf = psfield.getDoubleGaussian(bandnum, normalize=True)
info.update(dgpsf=dgpsf)
if psf == 'kl-pix':
# Pixelized KL-PSF
klpsf = psfield.getPsfAtPoints(bandnum, x0+W/2, y0+H/2)
# Trim symmetric zeros
sh,sw = klpsf.shape
while True:
if (np.all(klpsf[0,:] == 0.) and
np.all(klpsf[:,0] == 0.) and
np.all(klpsf[-1,:] == 0.) and
np.all(klpsf[:,-1] == 0.)):
klpsf = klpsf[1:-1, 1:-1]
else:
break
mypsf = PixelizedPSF(klpsf)
elif psf == 'kl-gm':
from emfit import em_fit_2d
from fitpsf import em_init_params
# Create Gaussian mixture model PSF approximation.
klpsf = psfield.getPsfAtPoints(bandnum, x0+W/2, y0+H/2)
S = klpsf.shape[0]
# number of Gaussian components
K = 3
w,mu,sig = em_init_params(K, None, None, None)
II = klpsf.copy()
II /= II.sum()
# HIDEOUS HACK
II = np.maximum(II, 0)
#print('Multi-Gaussian PSF fit...')
xm,ym = -(S/2), -(S/2)
if savepsfimg is not None:
plt.clf()
plt.imshow(II, interpolation='nearest', origin='lower')
plt.title('PSF image to fit with EM')
plt.savefig(savepsfimg)
res = em_fit_2d(II, xm, ym, w, mu, sig)
#print('em_fit_2d result:', res)
if res == 0:
# print('w,mu,sig', w,mu,sig)
mypsf = GaussianMixturePSF(w, mu, sig)
mypsf.computeRadius()
else:
# Failed! Return 'dg' model instead?
print('PSF model fit', psf, 'failed! Returning DG model instead')
psf = 'dg'
if psf == 'dg':
print('Creating double-Gaussian PSF approximation')
(a,s1, b,s2) = dgpsf
mypsf = NCircularGaussianPSF([s1, s2], [a, b])
if brightpsf:
print('Wrapping PSF in SdssBrightPSF')
(a1,s1, a2,s2, a3,sigmap,beta) = psfield.getPowerLaw(bandnum)
mypsf = SdssBrightPSF(mypsf, a1,s1,a2,s2,a3,sigmap,beta)
print('PSF:', mypsf)
timg = Image(data=image, invvar=invvar, psf=mypsf, wcs=wcs,
sky=skyobj, photocal=photocal,
name=('SDSS (r/c/f/b=%i/%i/%i/%s)' %
(run, camcol, field, bandname)),
time=TAITime(tai),
**imargs)
timg.zr = zr
return timg,info
def get_tractor_image(run, camcol, field, bandname,
sdssobj=None, release='DR7',
retrieve=True, curl=False,
psf='kl-gm', useMags=False,
roi=None,
roiradecsize=None,
roiradecbox=None,
nanomaggies=False,
savepsfimg=None, zrange=[-3,10]):
'''
Creates a tractor.Image given an SDSS field identifier.
If not None, roi = (x0, x1, y0, y1) defines a region-of-interest
in the image, in zero-indexed pixel coordinates. x1,y1 are
NON-inclusive; roi=(0,100,0,100) will yield a 100 x 100 image.
psf can be:
"dg" for double-Gaussian
"kl-gm" for SDSS KL-decomposition approximated as a Gaussian mixture
"roiradecsize" = (ra, dec, half-size in pixels) indicates that you
want to grab a ROI around the given RA,Dec.
Returns:
(tractor.Image, dict)
dict contains useful details like:
'sky'
'skysig'
'''
from astrometry.sdss import DR7, band_index
if sdssobj is None:
# Ugly
if release != 'DR7':
raise RuntimeError('We only support DR7 currently')
sdss = DR7(curl=curl)
else:
sdss = sdssobj
valid_psf = ['dg', 'kl-gm']
if psf not in valid_psf:
raise RuntimeError('PSF must be in ' + str(valid_psf))
# FIXME
rerun = 0
bandnum = band_index(bandname)
_check_sdss_files(sdss, run, camcol, field, bandname,
['fpC', 'tsField', 'psField', 'fpM'],
retrieve=retrieve)
fpC = sdss.readFpC(run, camcol, field, bandname)
hdr = fpC.getHeader()
fpC = fpC.getImage()
fpC = fpC.astype(np.float32) - sdss.softbias
image = fpC
(H,W) = image.shape
info = dict()
tai = hdr.get('TAI')
stripe = hdr.get('STRIPE')
strip = hdr.get('STRIP')
obj = hdr.get('OBJECT')
info.update(tai=tai, stripe=stripe, strip=strip, object=obj, hdr=hdr)
tsf = sdss.readTsField(run, camcol, field, rerun)
astrans = tsf.getAsTrans(bandnum)
wcs = SdssWcs(astrans)
#print('Created SDSS Wcs:', wcs)
X = interpret_roi(wcs, (H,W), roi=roi, roiradecsize=roiradecsize,
roiradecbox=roiradecbox)
if X is None:
return None,None
roi,hasroi = X
info.update(roi=roi)
x0,x1,y0,y1 = roi
# Mysterious half-pixel shift. asTrans pixel coordinates?
wcs.setX0Y0(x0 + 0.5, y0 + 0.5)
if nanomaggies:
zp = tsf.get_zeropoint(bandnum)
photocal = LinearPhotoCal(NanoMaggies.zeropointToScale(zp),
band=bandname)
elif useMags:
photocal = SdssMagsPhotoCal(tsf, bandname)
else:
photocal = SdssFluxPhotoCal()
psfield = sdss.readPsField(run, camcol, field)
sky = psfield.getSky(bandnum)
skysig = sqrt(sky)
skyobj = ConstantSky(sky)
zr = sky + np.array(zrange) * skysig
info.update(sky=sky, skysig=skysig, zr=zr)
fpM = sdss.readFpM(run, camcol, field, bandname)
gain = psfield.getGain(bandnum)
darkvar = psfield.getDarkVariance(bandnum)
skyerr = psfield.getSkyErr(bandnum)
invvar = sdss.getInvvar(fpC, fpM, gain, darkvar, sky, skyerr)
dgpsf = psfield.getDoubleGaussian(bandnum, normalize=True)
info.update(dgpsf=dgpsf)
if roi is not None:
roislice = (slice(y0,y1), slice(x0,x1))
image = image[roislice].copy()
invvar = invvar[roislice].copy()
if psf == 'kl-gm':
from emfit import em_fit_2d
from fitpsf import em_init_params
# Create Gaussian mixture model PSF approximation.
H,W = image.shape
klpsf = psfield.getPsfAtPoints(bandnum, x0+W/2, y0+H/2)
S = klpsf.shape[0]
# number of Gaussian components
K = 3
w,mu,sig = em_init_params(K, None, None, None)
II = klpsf.copy()
II /= II.sum()
# HIDEOUS HACK
II = np.maximum(II, 0)
#print('Multi-Gaussian PSF fit...')
xm,ym = -(S/2), -(S/2)
if savepsfimg is not None:
plt.clf()
plt.imshow(II, interpolation='nearest', origin='lower')
plt.title('PSF image to fit with EM')
plt.savefig(savepsfimg)
res = em_fit_2d(II, xm, ym, w, mu, sig)
print('em_fit_2d result:', res)
if res == 0:
# print('w,mu,sig', w,mu,sig)
mypsf = GaussianMixturePSF(w, mu, sig)
mypsf.computeRadius()
else:
# Failed! Return 'dg' model instead?
print('PSF model fit', psf, 'failed! Returning DG model instead')
psf = 'dg'
if psf == 'dg':
print('Creating double-Gaussian PSF approximation')
(a,s1, b,s2) = dgpsf
mypsf = NCircularGaussianPSF([s1, s2], [a, b])
timg = Image(data=image, invvar=invvar, psf=mypsf, wcs=wcs,
sky=skyobj, photocal=photocal,
name=('SDSS (r/c/f/b=%i/%i/%i/%s)' %
(run, camcol, field, bandname)))
timg.zr = zr
return timg,info
def _get_sources(run, camcol, field, bandname='r', sdss=None, release='DR7',
objs=None,
retrieve=True, curl=False, roi=None,
radecroi=None,
radecrad=None,
bands=None,
badmag=25, nanomaggies=False,
getobjs=False, getsourceobjs=False, getobjinds=False,
extrabands=None,
fixedComposites=False,
forcePointSources=False,
useObjcType=False,
objCuts=True,
classmap={},
ellipse=GalaxyShape,
cutToPrimary=False):
'''
If set,
radecrad = (ra,dec,rad)
returns sources within "rad" degrees of the given RA,Dec (in degrees)
center.
WARNING, this method alters the "objs" argument, if given.
Consider calling objs.copy() before calling.
-"bandname" is the SDSS band used to cut on position, select
star/gal/exp/dev, and set galaxy shapes.
-"bands" are the bands to include in the returned Source objects;
they will be initialized from the SDSS bands.
-"extrabands" are also included in the returned Source objects;
they will be initialized to the SDSS flux for either the first of
"bands", if given, or "bandname".
'''
from astrometry.sdss import (DR7, DR8, DR9, band_names, band_index,
photo_flags1_map)
# brightPointSourceThreshold=0.):
if sdss is None:
dr = dict(DR7=DR7, DR8=DR8, DR9=DR9)[release]
sdss = dr(curl=curl)
drnum = sdss.getDRNumber()
isdr7 = (drnum == 7)
if bands is None:
bands = band_names()
bandnum = band_index(bandname)
bandnums = np.array([band_index(b) for b in bands])
bandnames = bands
if extrabands is None:
extrabands = []
if objs is None:
from astrometry.util.fits import fits_table
if isdr7:
# FIXME
rerun = 0
_check_sdss_files(sdss, run, camcol, field, bandnum,
['tsObj', 'tsField'],
retrieve=retrieve, tryopen=True)
tsf = sdss.readTsField(run, camcol, field, rerun)
objfn = sdss.getPath('tsObj', run, camcol, field,
bandname, rerun=rerun)
else:
_check_sdss_files(sdss, run, camcol, field, bandnum, ['photoObj'],
tryopen=True, retrieve=retrieve)
objfn = sdss.getPath('photoObj', run, camcol, field)
objs = fits_table(objfn)
if objs is None:
print('No sources in SDSS file', objfn)
return []
objs.index = np.arange(len(objs))
if getobjs:
allobjs = objs.copy()
if roi is not None:
x0,x1,y0,y1 = roi
# FIXME -- we keep only the sources whose centers are within
# the ROI box. Should instead do some ellipse-overlaps
# geometry.
x = objs.colc[:,bandnum]
y = objs.rowc[:,bandnum]
objs.cut((x >= x0) * (x < x1) * (y >= y0) * (y < y1))
if radecroi is not None:
r0,r1,d0,d1 = radecroi
objs.cut((objs.ra >= r0) * (objs.ra <= r1) *
(objs.dec >= d0) * (objs.dec <= d1))
if radecrad is not None:
from astrometry.libkd.spherematch import match_radec
(ra,dec,rad) = radecrad
I,J,d = match_radec(ra, dec, objs.ra, objs.dec, rad)
objs.cut(J)
del I
del d
if objCuts:
# Only deblended children;
# No BRIGHT sources
bright = photo_flags1_map.get('BRIGHT')
objs.cut((objs.nchild == 0) * ((objs.objc_flags & bright) == 0))
if cutToPrimary:
objs.cut((objs.resolve_status & 256) > 0)
if isdr7:
objs.rename('phi_dev', 'phi_dev_deg')
objs.rename('phi_exp', 'phi_exp_deg')
objs.rename('r_dev', 'theta_dev')
objs.rename('r_exp', 'theta_exp')
# SDSS and Tractor have different opinions on which way this rotation goes
objs.phi_dev_deg *= -1.
objs.phi_exp_deg *= -1.
# MAGIC -- minimum size of galaxy.
objs.theta_dev = np.maximum(objs.theta_dev, 1./30.)
objs.theta_exp = np.maximum(objs.theta_exp, 1./30.)
if forcePointSources:
Lstar = np.ones(len(objs), float)
Lgal = np.zeros(len(objs), float)
Ldev = Lexp = Lgal
else:
if useObjcType:
objs.cut(np.logical_or(objs.objc_type == 6,
objs.objc_type == 3))
Lstar = (objs.objc_type == 6)
Lgal = (objs.objc_type == 3)
else:
Lstar = (objs.prob_psf[:,bandnum] == 1) * 1.0
Lgal = (objs.prob_psf[:,bandnum] == 0)
if isdr7:
fracdev = objs.fracpsf[:,bandnum]
else:
fracdev = objs.fracdev[:,bandnum]
Ldev = Lgal * fracdev
Lexp = Lgal * (1. - fracdev)
if isdr7:
if nanomaggies:
raise RuntimeError('Nanomaggies not supported for DR7 (yet)')
def lup2bright(lups):
counts = [tsf.luptitude_to_counts(lup,j)
for j,lup in enumerate(lups)]
counts = np.array(counts)
bright = _getBrightness(counts, tsf, bandnames, extrabands)
return bright
flux2bright = lup2bright
starflux = objs.psfcounts
compflux = objs.counts_model
devflux = objs.counts_dev
expflux = objs.counts_exp
def comp2bright(lups, Ldev, Lexp):
counts = [tsf.luptitude_to_counts(lup,j)
for j,lup in enumerate(lups)]
counts = np.array(counts)
dcounts = counts * Ldev
ecounts = counts * Lexp
dbright = _getBrightness(dcounts, tsf, bands, extrabands)
ebright = _getBrightness(ecounts, tsf, bands, extrabands)
return dbright, ebright
else:
def nmgy2bright(flux):
if len(bandnums):
flux = flux[bandnums]
else:
flux = flux[np.array([bandnum])]
bb = bandnames + extrabands
if nanomaggies:
if len(extrabands):
if len(bandnums) == 0:
# Only "extrabands", no SDSS bands.
flux = np.zeros(len(extrabands)) + flux[0]
else:
flux = np.append(flux, np.zeros(len(extrabands)))
bright = NanoMaggies(order=bb, **dict(zip(bb, flux)))
else:
I = (flux > 0)
mag = np.zeros_like(flux) + badmag
mag[I] = sdss.nmgy_to_mag(flux[I])
if len(extrabands):
mag = np.append(mag, np.zeros(len(extrabands)) + badmag)
bright = Mags(order=bb, **dict(zip(bb,mag)))
return bright
def comp2bright(flux, Ldev, Lexp):
dflux = flux * Ldev
eflux = flux * Lexp
dbright = nmgy2bright(dflux)
ebright = nmgy2bright(eflux)
return dbright, ebright
flux2bright = nmgy2bright
starflux = objs.psfflux
compflux = objs.cmodelflux
devflux = objs.devflux
expflux = objs.expflux
sources = []
nstars, ndev, nexp, ncomp = 0, 0, 0, 0
isources = []
ptsrcclass = classmap.get(PointSource, PointSource)
for i in range(len(objs)):
if Lstar[i]:
pos = RaDecPos(objs.ra[i], objs.dec[i])
flux = starflux[i,:]
bright = flux2bright(flux)
# This should work, I just don't feel like testing it now...
# if brightPointSourceThreshold:
# ps = SdssPointSource(pos, bright, thresh=brightPointSourceThreshold)
# else:
# ps = PointSource(pos, bright)
sources.append(ptsrcclass(pos, bright))
nstars += 1
isources.append(i)
continue
hasdev = (Ldev[i] > 0)
hasexp = (Lexp[i] > 0)
iscomp = (hasdev and hasexp)
pos = RaDecPos(objs.ra[i], objs.dec[i])
if iscomp:
flux = compflux[i,:]
elif hasdev:
flux = devflux[i,:]
elif hasexp:
flux = expflux[i,:]
else:
print('Skipping object with Lstar = %g, Ldev = %g, Lexp = %g (fracdev=%g)'
% (Lstar[i], Ldev[i], Lexp[i], fracdev[i]))
continue
isources.append(i)
if iscomp:
if fixedComposites:
bright = flux2bright(flux)
fdev = (Ldev[i] / (Ldev[i] + Lexp[i]))
else:
dbright,ebright = comp2bright(flux, Ldev[i], Lexp[i])
else:
bright = flux2bright(flux)
if hasdev:
re = objs.theta_dev [i,bandnum]
ab = objs.ab_dev [i,bandnum]
phi = objs.phi_dev_deg[i,bandnum]
dshape = ellipse(re, ab, phi)
if hasexp:
re = objs.theta_exp [i,bandnum]
ab = objs.ab_exp [i,bandnum]
phi = objs.phi_exp_deg[i,bandnum]
eshape = ellipse(re, ab, phi)
if iscomp:
if fixedComposites:
gal = FixedCompositeGalaxy(pos, bright, fdev, eshape, dshape)
else:
gal = CompositeGalaxy(pos, ebright, eshape, dbright, dshape)
ncomp += 1
elif hasdev:
gal = DevGalaxy(pos, bright, dshape)
ndev += 1
elif hasexp:
gal = ExpGalaxy(pos, bright, eshape)
nexp += 1
sources.append(gal)
print('Created', ndev, 'deV,', nexp, 'exp,', ncomp, 'composite',)
print('(total %i) galaxies and %i stars' % (ndev+nexp+ncomp, nstars))
if not (getobjs or getobjinds or getsourceobjs):
return sources
if nstars + ndev + nexp + ncomp < len(objs):
objs = objs[np.array(isources)]
rtn = [sources]
if getobjs:
rtn.append(allobjs)
if getobjinds:
rtn.append(objs.index if len(objs) else np.array([]))
if getsourceobjs:
rtn.append(objs)
return rtn
